"forex Algorithmic Trading: Automated Strategies For Profitable Trading Down Under"

 "forex Algorithmic Trading: Automated Strategies For Profitable Trading Down Under" - The foreign exchange market (forex) is the most liquid market in the world. Learn from a software developer's first-hand experience in creating algorithmic forex trading strategies—and more—in this trading guide.

The authors are proven experts in their field and write about topics in which they have proven expertise. All of our content is peer-reviewed and validated by experts in the field.

"forex Algorithmic Trading: Automated Strategies For Profitable Trading Down Under"

Rogelio is a flexible and motivated full-stack engineer with more than 13 years of experience working across multiple languages, frameworks and platforms.

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Editor's note: This article was updated by our editorial team on July 21, 2022. It has been modified to include recent sources and align with current editorial standards.

As you may know, the foreign exchange (forex or FX) market is used to trade between currency pairs. But you may not know that it is the most liquid market in the world. (Yes, even compared to crypto, forex is generally considered safer and more profitable.)

A few years ago, out of curiosity, I took my first steps into the world of algorithmic forex trading by creating a demo account and playing simulations (with fake money) on the Meta Trader 4 trading platform.

After a week of "trading", I had almost doubled my money. Motivated by my successful algorithmic trading, I dug deeper and eventually joined several FX forums. Soon, I was spending hours reading about algorithmic forex trading systems (rule sets that determine whether you should buy or sell), custom indicators, market sentiment, and more.

Excellent Algorithmic Trading Platforms

Around that time, by coincidence, I heard that someone was trying to find a software developer to create a simple, automated forex trading system. This was back in my college days when I was learning about concurrent programming in Java (threads, semaphores and more). I figured this automated forex trading system couldn't be much more complicated than my advanced data science course, so I applied for the job and joined.

The client wanted algorithmic trading software built with MQL4, a functional programming language used by the Meta Trader 4 platform to perform stock-related actions.

MQL5 has since been released. As you might expect, it addresses some of MQL4's issues and has more built-in features that make life easier.

The role of the trading platform (Meta Trader 4, in this case) is to provide a connection to a forex broker. The broker then provides a platform with real-time market information and executes buy/sell orders. For readers unfamiliar with algorithmic forex trading, here is the information provided by the data feed:

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Through Meta Trader 4, you can access all this data with internal functions, accessible in different timeframes: M1 (every minute), M5 (every five minutes), M15, M30, H1 (hourly), H4, D1 (daily), W1 (weekly) and MN (monthly).

The movement of the current price is called a tick. A tick is a change in the bid or ask price for a currency pair. During active markets, there may be several ticks per second. During slow purchases, minutes may pass without a tick. The tick is the heartbeat of a forex trading robot.

When you place an order through such a platform, you buy or sell a specific volume of a specific currency. You also set stop and take profit limits. The stop-loss limit is the maximum amount of pips (price fluctuations) you can afford to lose before exiting a trade. Profit limit is the amount of pips you will accumulate in your favor before cashing out.

If you want to learn more about the basics of trading (eg pips, order types, spreads, slippage, buy orders and more), BabyPips is a great resource.

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The client's algorithmic trading specifications were simple: a forex robot based on two indicators. Historically, indicators are very useful when trying to define a market situation and make trading decisions, as they are based on past data (eg the highest price price in the last

Days). Many come built into Meta Trader 4. However, the indicators of interest to my client came from a custom forex trading system.

The client wanted to trade whenever two of these custom indicators intersected and only at a certain angle.

The start function is the heart of any MQL4 program. It is executed every time the market moves (so, this function is executed once per tick). This happens regardless of a given time frame. For example, you could operate on the H1 time frame (one hour), but the start function would run many thousands of times per hour.

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Once I built my algorithmic trading system, I wanted to know if it was behaving correctly and if the forex trading strategy it was using was good.

Backtesting is the process of testing a specific system (automated or not) under past events. In other words, you test your system using the past as a proxy for the present.

MT4 comes with an acceptable tool to backtest a forex trading strategy (today, there are more professional tools that offer more functionality). To get started, you set the time frames and run your program in a simulation. the tool will simulate each tick, knowing that for each unit it should open at a specific price, close at a specific price, and reach specific highs and lows.

After comparing the program's actions with historical values, you'll have a good sense of whether it's running correctly or not.

Pick The Right Algorithmic Trading Software

Through backtesting, I had checked the return ratio of the FX robot for some random time intervals. I knew that my client was not going to get rich with the trading strategy used - the selected indicators, along with the logic of the decision, were not profitable. Here are the results of running the program through the M15 window for 164 functions:

A caveat: Saying that a system is "profitable" or "unprofitable" is not always accurate. Often, systems are (un)profitable for periods of time based on the "mood" of the market, which can follow a number of chart patterns:

Although the backtest had made me wary of the usefulness of this FX bot, I was intrigued when I started playing with its external parameters and noticed big differences in the overall performance ratio. This is known as

I did some rough tests to try to infer the importance of external parameters on the return ratio and came up with this:

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You may think, as I did, that you should use parameter A. But the decision is not as simple as it seems. In particular, note the unpredictability of the A parameter: For small error values, its performance changes dramatically. In other words, parameter A is very likely to overpredict future outcomes, since any uncertainty—any drift—will lead to worse performance.

But indeed, the future is uncertain! And so the return of parameter A is also uncertain. The best option, in fact, is to rely on the unexpected. Often, a parameter with lower peak performance but superior predictability (less variation) will be preferable to a parameter with high performance but poor predictability.

The only thing you can know for sure is that you don't know the future of the market, and it's a mistake to assume you know how the market will perform based on past data. Therefore, you need to recognize this unpredictability in your forex predictions.

It is a mistake to assume that you know how the market will perform based on past data.

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This does not necessarily mean that we should use parameter B because even the lower returns of parameter A perform better than the returns of parameter B. Optimizing parameters can lead to tests that overestimate possible future outcomes, and such thinking is not obvious.

From my first experience with algorithmic forex trading, I have built many automated trading systems for clients and I can tell you that there is always room for exploration and further forex analysis. For example, I recently built a system based on finding the so-called "big fish" movements: huge dot variations in very small units of time. This is a subject that fascinates me.

Building your own FX simulator is a great option to learn more about trading the forex market and the possibilities are endless. For example, you could try to decipher the probability distribution of price swings as a function of volatility in a market (EUR/USD for example) or build a Monte Carlo simulation model using the distribution by state of volatility, using whatever degree of precision you prefer . I'll leave this as an exercise for the

The world of forex can be overwhelming at times, but I encourage you to explore your own algorithmic forex trading strategy.

The World Of High Frequency Algorithmic Trading

Today, there is a huge pool of tools for building, testing, and improving forex trading system automations: Trading Blox for testing, NinjaTrader for trading, and OCaml for programming, to name a few.

I have read extensively about the mysterious world that is the forex market. Here are some resources for developers and avid readers: Algorithmic trading is an order execution process that uses automated and pre-programmed trading instructions to take into account variables such as price, time and volume. An algorithm is a set of instructions for solving a problem. Computer algorithms send small portions of it

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